Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
Find roles through people you trust, and message a verified founder or page admin about your interest.
Responsibility:
Run backtests and statistical checks, and study how factor performance varies across market regimes.
Automate monthly signal production and suggest improvements to the process.
Develop HMM, regime-switching and reinforcement learning models where appropriate.
Build dashboards to keep track of data quality and strategy performance.
构建干净的历史数据集,并维护时间点数据,以确保研究使用准确且完全可追溯的信息。
Requirement:
Master’s degree or PhD in machine learning, computer science, statistics or a related quantitative discipline. Specialization in reinforcement learning is highly desirable.
5+ years working experience in quantitative research, data science, or a related field (industry or academic).
Strong programming skills in Python; experience with machine learning libraries.
Quantitative Modeling: Familiarity with quantitative modeling, portfolio construction, and equity markets.
Data Handling: Experience working with large, complex, and alternative datasets.
Excellent verbal and written communication skills in English, with the ability to present complex ideas to both technical and non-technical audiences.
Collaboration: Demonstrated ability to work effectively in a team environment.
Strong problem-solving skills and intellectual curiosity; ability to drive research projects independently.
硕士学位或博士学位,机器学习、计算机科学、统计学或相关定量学科专业。
具有5年以上定量研究、数据科学或相关领域(行业或学术)的工作经验。
具有优秀的技术能力,在Python中拥有较强的编程技能并拥有机器学习库的经验。
熟悉定量建模、投资组合构建和股票市场。
拥有处理大型、复杂和替代数据集的经验。
优秀的英文口头和书面沟通技巧,能够向技术和非技术受众提出复杂的想法。
展现出在团队环境中有效工作的能力。
强大的解决问题的技能和智力好奇心;独立推动研究项目的能力。